Abstract
ObjectiveTo develop a nomogram for predicting axillary lymph node (ALN) metastases using the breast imaging reporting and data system (BI-RADS) ultrasound lexicon.MethodsA total of 703 patients from July 2015 to January 2018 were included in this study as a primary cohort for model construction. Moreover, 109 patients including 51 pathologically confirmed N1 patients (TNM staging) and 58 non-metastatic patients were recruited as an external validation cohort from March 2018 to August 2019. Ultrasound images and clinical information of these patients were retrospectively reviewed. The ultrasonic features based on the BI-RADS lexicon were extracted by two radiologists. The features extracted from the primary cohort were used to develop a nomogram using multivariate analysis. Internal and external validations were performed to evaluate the predictive efficacy of the nomogram.ResultsThe nomogram was based on two features (size, lesion boundary) and showed an area under the curve of 0.75 (95% confidence interval [CI], 0.70–0.79) in the primary cohort and 0.91 (95% CI, 0.84–0.97) in the external validation cohort; it achieved an 88% sensitivity in N1 patients.ConclusionThe nomogram based on BI-RADS ultrasonic features can predict breast cancer ALN status with relatively high accuracy. It has potential clinical value in improving the sensitivity and accuracy of the preoperative diagnosis of ALN metastases, especially for N1 patients.
Highlights
Breast cancer, posing a serious threat to women’s health and social economy, has drawn great attention from researchers for years [1]
Prediction of Breast Cancer Metastasis currently recognized method for identifying Axillary lymph node (ALN) status is sentinel lymph node biopsy (SLNB), which is performed during surgery and requires pathological diagnosis
We summarize the ultrasonic features of the malignant lesions using the breast imaging reporting and data system (BI-RADS) lexicon, the widely accepted standard for defining ultrasonic feature of breast lesions [14]
Summary
Breast cancer, posing a serious threat to women’s health and social economy, has drawn great attention from researchers for years [1]. Axillary lymph node (ALN) status plays an essential role in treatment planning for breast cancer [2], being the most significant prognostic indicator for early stage patients [3]. Preoperative staging of ALN status can make a way for optimized clinical decision making. Prediction of Breast Cancer Metastasis currently recognized method for identifying ALN status is sentinel lymph node biopsy (SLNB), which is performed during surgery and requires pathological diagnosis. Axillary ultrasound (US) is commonly recommended for all patients with breast cancer to evaluate ALN status preoperatively [6, 7]. It is crucial to improve the preoperative diagnostic accuracy of US in identifying ALN metastases, especially for patients with a minimal number of abnormal nodes
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